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Effect of powdery layer coverage on the sticking and rebound behaviors of ash particle impaction: A DEM study
期刊论文
POWDER TECHNOLOGY, 2021, 卷号: 382, 页码: 388-397
作者:
Zhu, Runru
;
Li, Gengda
;
Zhang, Yiyang
;
Song, Minhang
;
Huang, Yun
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2021/03/29
Impaction
Powdery layer
DEM
Sticking probability
Restitution coefficient
Two-Dimensional Silicon Fingerprints Reveal Dramatic Variations in the Sources of Particulate Matter in Beijing during 2013-2017
期刊论文
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2020, 卷号: 54, 期号: 12, 页码: 7126-7135
作者:
Yang, Xuezhi
;
Lu, Dawei
;
Tan, Jihua
;
Sun, Xu
;
Zhang, Qinghua
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  |  
浏览/下载:18/0
  |  
提交时间:2021/09/14
Nondestructive assessment of the compressive strength of concrete with high volume slag
期刊论文
Materials Characterization, 2020, 卷号: 162
作者:
Yang, Yonggan
;
Zhan, Binggen
;
Wang, Jingfeng
;
Zhang, Yunsheng
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  |  
浏览/下载:5/0
  |  
提交时间:2020/11/14
Aggregates
Compressive strength
Computerized tomography
Concrete aggregates
Particle size
Polymethyl methacrylates
Pore structure
Slags
X rays
Coarse aggregates
Compressive strength of concrete
Mercury intrusion porosimetry
Nondestructive assessment
Rebound value
Strength curves
X-ray computed tomography
X-ray CT
Experimental Study of Mechanical Behavior of Interlayer Staggered Zone under Cyclic Loading and Unloading Condition
期刊论文
INTERNATIONAL JOURNAL OF GEOMECHANICS, 2020, 卷号: 20, 期号: 3, 页码: 12
作者:
Duan, Shudian
;
Jian, Quan
;
Xu, Dingping
;
Liu, Guofeng
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  |  
浏览/下载:25/0
  |  
提交时间:2021/05/25
Interlayer staggered zone (ISZ)
Cyclic loading and unloading
Volume expansion
Rebound modulus
Dilatation angle
Hysteresis loop
Decoupling and driving forces of industrial carbon emission in a coastal city of Zhuhai, China
期刊论文
ENERGY REPORTS, 2019, 卷号: 5, 页码: 1589-1602
作者:
Feng, Jing-Chun
;
Zeng, Xue-Lan
;
Yu, Zhi
;
Bian, Yong
;
Li, Wei-Chi
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  |  
浏览/下载:14/0
  |  
提交时间:2020/10/29
Energy consumption
Carbon emission
Decoupling
Driving forces
Industrial sector
City-level
Decomposition of rebound effect: An energy-specific, general equilibrium analysis in the context of China
期刊论文
APPLIED ENERGY, 2018, 卷号: 221, 页码: 280-298
作者:
Zhou, Meifang[1]
;
Liu, Yu[2]
;
Feng, Shenghao[3]
;
Liu, Yang[4]
;
Lu, Yingying[5]
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  |  
浏览/下载:3/0
  |  
提交时间:2019/04/22
Rebound effect decomposition
Energy-specific
CGE model
Sectoral contribution
Output effect
Substitution effect
Correlation of UCS Rating with Schmidt Hammer Surface Hardness for Rock Mass Classification
期刊论文
Rock Mechanics and Rock Engineering, 2017, 卷号: 50, 期号: 1, 页码: 195-203
作者:
Wang, Hu
;
Lin, Hang*
;
Cao, Ping
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  |  
浏览/下载:7/0
  |  
提交时间:2019/12/03
Rebound value
Rock mass classification
Schmidt hammer
Surface hardness
Uniaxial compressive strength
An analysis of the resilience capacity of soils in North China: a study on land subsidence treatment
期刊论文
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2014, 卷号: 73, 期号: 3, 页码: 723-731
作者:
Wang, Xiu-yan
;
Sun, Lin
;
Wang, Zhi-liang
;
Liu, Chang-li
;
Zhang, Yun
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  |  
浏览/下载:4/0
  |  
提交时间:2018/11/12
Soil unloading rebound
Resilience capacity
Deep groundwater overexploitation
Controlling subsidence
North China
海螺沟冰川退缩迹地风化——成土过程与土壤磷形态研究
学位论文
博士, 北京: 中国科学院研究生院, 2014
作者:
周俊
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  |  
浏览/下载:90/0
  |  
提交时间:2015/03/03
早期风化过程
风化速率
磷释放
磷生物有效性
磷形态
Prediction of concrete strength using fuzzy neural networks
会议论文
Haikou, China, June 18, 2011 - June 20, 2011
作者:
Xu, Jing
;
Wang, Xiuli
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  |  
浏览/下载:5/0
  |  
提交时间:2020/11/15
Algebra
Building materials
Civil engineering
Compressive strength
Construction equipment
Forecasting
Fuzzy inference
Fuzzy logic
Fuzzy systems
Learning algorithms
Least squares approximations
Mathematical models
Network architecture
Adaptive neuro-fuzzy inference system
Automatic-learning
Average relative error
Compressive strength of concrete
Concrete strength
Concrete strength prediction
Condition parameters
Expert experience
Fuzzy logic inference
Fuzzy Neural Networks (FNN)
Gradient Descent method
Hybrid-learning algorithm
Input and outputs
Input-output data
Intelligent prediction
Least squares methods
Parameter set
Power functions
Practical engineering
Prediction model
Rebound value
Relative standard error
Specific equations
Strength values
Takagi-sugeno
Test results
Training patterns
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